Abstract
An asset pricing test is just variable selection confined to the intercepts. Framing the testing problem as variable selection facilitates development of a new Bayesian multivariate test that strikes a balance between the extreme of tests based purely on statistical significance (e.g., Gibbons, Ross, and Shanken (GRS) (1989)) and the extreme of tests based purely on economic significance (i.e., just look at the intercepts). Our procedure jointly tests for statistical and economic significance while explicitly accounting for the fact that, since all models are false, no model can satisfy a sharp null hypothesis. In addition, our most important prior represents the largest average pricing error considered economically insignificant. This prior’s simple interpretation is a key feature of our approach. We demonstrate our test on both simulated economies and actual data and compare it to the GRS test.
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Stevens, R.L. (1997). Variable Selection Tests of Asset Pricing Models. In: Gatsonis, C., Hodges, J.S., Kass, R.E., McCulloch, R., Rossi, P., Singpurwalla, N.D. (eds) Case Studies in Bayesian Statistics. Lecture Notes in Statistics, vol 121. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-2290-3_6
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DOI: https://doi.org/10.1007/978-1-4612-2290-3_6
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